Engineering of Automated Systems with Mechatronic Objects

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1 Engineering of Automated Systems with Mechatronic Objects On Cyber Physical Systems, intelligent Units, Industrie 4.0 Components and other granular and decentralized elements in automation engineering Institute of Industrial Automation Technology and Software Engineering (IAS) Prof. Dr.-Ing. Michael Weyrich 27. May IAS, Stuttgart University

2 Abstract: Automation technology has trigged a lot of changes in manufacturing, automotive and urban life. Today we seem to be gradually approaching tipping points which might trigger disruptive innovation in the future. In automation engineering, many industrial automation systems are configured rather than designed. There is a tendency towards so-called mechatronic objects or intelligent units which are envisioned as building blocks for the design of automation systems. This presentation discusses research questions to identify such objects / units, their configuration and coordination using multi-agent systems IAS, Universität Stuttgart 2

3 Institute of Industrial Automation and Software Engineering (IAS); Faculty of Computer Science, Electrical Engineering and Information Technology of Stuttgart University Research and Teaching of the Institute is focused on software systems for automation engineering and is based on our background in information technology, software and electronics. We are researching towards applications of automated manufacturing, automotive and consumers products IAS, Stuttgart University 3

4 5 years 10 years Prof. Dr.-Ing. Michael Weyrich Resume Education in the area of mechatronics Studies of Electronic Engineering and Control Engineering at University of Applied Science (Saarbrücken), Ruhr University (Bochum) and University of Westminster (London) Doctorate, RWTH (Aachen) in Mechanical Engineering Daimler Member of the exchange group research and technology Digital Factory Powertrain and Head of Function CAx Process Chain Production Head of Department Engineering Services, Bangalore (India) Siemens Automation & Drives /Motion Control Head of Department, direct Report to Head of Business Unit University Professor Chair of Manufacturing Automation, University of Siegen Institute of industrial Automation Technology and Software Engineering, University of Stuttgart 2014 IAS, Stuttgart University 4

5 Contents Vision State-of-the-Art: Technologies in Automotive Research activities Example of Smart Factory and Agent-based control Identification of Mechatronic Objects Moving Design to Runtime Conclusion 2014 IAS, Stuttgart University 5

6 Contents Vision State-of-the-Art: Technologies in Automotive Research activities Example of Smart Factory and Agent-based control Identification of Mechatronic Objects Moving Design to Runtime Conclusion 2014 IAS, Stuttgart University 6

7 Vision: Mechatronic Objects / Smart Units / Intelligent Nodes Source of picture: Internet Mapping Project Assumption 1: Objects are more and more enabled by means of communication Assumption 2: New services are arising using networked information Future Trend: The Internet of Things and Services is automating the world. Unified interfaces for networking semantics Configuration instead of development Functional systems description Requirement definition aided by architectural assistant Integrated Know-how inside objects Knowledge based Engineering Virtual Evaluation Libraries with basic module / building blocks 2014 IAS, Stuttgart University 7

8 Source: Based on : Gausemeier, Univ. Paderborn Prof. Dr.-Ing. Michael Weyrich Mechatronic Objects, Cyber-physical Systems, Smart, networked Systems as a game-changer: New ways of cooperation among distributed and intelligent units. Interaction with human in a hybrid reality. Communication Infrastructure Cooperative Systems Information processing Humanmachine interface Human Control Actuators Object / Unit Sensors Environment Systems 2014 IAS, Stuttgart University 8

9 Contents Vision State-of-the-Art: Technologies in Automotive Research activities Example of Smart Factory and Agent-based control Identification of Mechatronic Objects Moving Design to Runtime Conclusion 2014 IAS, Stuttgart University 9

10 Source of pictures: Daimler AG Prof. Dr.-Ing. Michael Weyrich Networking Technology of the Car changes the process of Development The number of ECU (Electronic control units), signals and bus systems is increasing Complexity of Electric / Electronics and software increases due to driver assistant systems and connected cars Process improvement and quality management in development (AUTOSAR Standard) Model-based development and simulation (SiL, HiL) 2014 IAS, Stuttgart University Number Example Daimler (E class) (W219) 92 control units (ECU) 2002 (W211) 14 bus systems Increasing number of signals (W221) (W212 MOPF) 10

11 Source of picture: Vector Consulting GmbH Prof. Dr.-Ing. Michael Weyrich Example Automotive Software Development Management of Electric / Electronic and Software Complexity aided by Design Tools Definition of Requirements Logical structuring into blocks Design of Software Architecture Implementation of Software Components Design of Electric / Electronic Hardware Development of ECUs Circuit diagrams Wire harness Etc. Hardware Design and spacial distribution Example of PREEvision modelling tool (Vector Informatics) 2014 IAS, Stuttgart University 11

12 Contents Vision State-of-the-Art: Technologies in Automotive Research activities Example of Smart Factory and Agent-based control Identification of Mechatronic Objects Moving Design to Runtime Conclusion 2014 IAS, Stuttgart University 12

13 Examples for Smart Units Smart Units are conceived by engineers and dedicated towards special application thereby fulfilling a particular customer value Intelligent Bin requests for a refill on its own ibin is counts the parts using an integrated camera The system interacts with the Cloud for part logistics Source: Fraunhofer IML, Prof. Dr. Michael ten Hompel 2014 IAS, Stuttgart University 13

14 Source: VDI, Hypotheses and fields of action: Opportunities form the perspective of automation technology, April 2013 Prof. Dr.-Ing. Michael Weyrich (Partial) Decentralization of the Architecture The level structure in automation (so-called automation pyramid) is dissolving Decentralized services are self-organizing and any hierarchy becomes blurred Real-time Systems remain however for some time on the bottom field level in the close future 2014 IAS, Stuttgart University 14

15 Scource: [Christian Diedrich, OvGU] Prof. Dr.-Ing. Michael Weyrich Case Study: Industrie 4.0 Demonstrator Cooperation between university institutes of the Automation Community Application Scenario My Yogurt Individual Product Configuration: Customers can order various amounts and flavors of yogurt via the internet. The yogurt is produced using different machines nation wide. Diagnosis of the distributed machinery: In the event of system failure of similar machines, an inquiry can be launched to obtain information on how the incident was resolved at another system. This approach can also be deployed for preventive maintenance IAS, Stuttgart University LS Informatik 11 RWTH Aachen Industrie 4.0 Demonstrator DFKI Kaiserlautern IAT HSU Hamburg IAS Universität Stuttgart Connected Verbundene machinery Anlagen Systems IFAT & ifak OvGU Magdeburg AIS TU München IAI TU Dresden 15

16 Scource: [Christian Diedrich, OvGU] Prof. Dr.-Ing. Michael Weyrich Case Study: What is special? Requirements Configuration of products with interactive resource allocation Diagnosis to improve reliability Reliable and easy to use by operators Re-configurable in the sense of interoperability, adaptivity and ad-hoc cooperation Technology Scheduling, Modelling of Processes Apps for human machine communication Service-oriented Architecture Network Management - Web Based Enterprise Management Cloud-Services for validation of embedded systems 2014 IAS, Stuttgart University 16

17 Case Study: Manufacturing Management and Scheduling Decentral System Topology coordinated by an online marked place concept Scheduling and job distribution Resource allocation and subcontracting Consideration of special aspects such as energy efficiency Quick integration of sub components (I40 Components) into the system T n T 4 Market place T 3 T1 T 2 T 1, T 2,, T n : dezentral I40 Components 2013 IAS, Universität Stuttgart 17

18 Decentralization of Architecture Hierarchies are fading and borders become blur Decentralized services are partially self-organised by agents Assignment of production jobs Reconfiguration Diagnosis Documentation Services for human machine Communication (Apps) Quality Control Condition Monitoring Coordination layer: Agents with directory of services and data processing Field Level (Real time level): Process Control, Sensors, Actuators etc IAS, Stuttgart University 18

19 Contents Vision State-of-the-Art: Technologies in Automotive Research activities Example of Smart Factory and Agent-based control Identification of Mechatronic Objects Moving Design to Runtime Conclusion 2014 IAS, Stuttgart University 19

20 How to identify the Modules? Top-down analysis of existing systems to identify base elements of existing systems Consideration of the domian s mechanical design, electronics and software Modules should fulfill a defined functionality Products or de-facto standardized subsystems which are efficient and well evaluated 20

21 Grouping by sorting the structure diagonal 2013 IAS, Universität Stuttgart 21

22 Identification of Modules using the Design Structure Matrix (DSM) Elements Small units e.g. from a bill of materials Is this component depended to the other component to fulfill a function? Image acquisition module Parts handling module Control module Interfaces are related to elements without allocation to modules Matrix after clustering: Camera-interface Image sensor Drive testing part rotation Image analysis software Screw-gripper Control lifting-turn-unit Drive Turning Drive Lifting Control illumination Control Rotary indexing table Control testing part rotation HMI PLC Drive for Rotary indexing table Pneumatics testing system Lifting-turning-unit Illumination Adaptor testing part Rotary indexing table Camera body Guidance for sorting of testing part Digital I/O Electronic units Control software Safety equipment Control centrifugal feeder Machine frame Separation DC motor centrifugal feeder Frame of centrifugal feeder Drum Driveshaft of centrifugal feeder Interaction Weight Required 2 Desired 1 Indifferent 0 mechtronical module standalone module Inspection support module distributed links intersectional links Supporting and Saftey module Parts feeding module Elements are grouped together as modules 22

23 Modularization for Engineering A Web-Tool is available for data processing, clustering and value analysis Clustering P-Median model Utility value - Bill of material - I/O listings - CAD data - Third party products Modules and components Definition of module by DSM K 1 K 3 K 4 K 5 K 2 K K K K K Software tool Basic Design Knowledge Encapsulated knowledge Hardware Java, PHP, MySQL; Open Model Sphere Information Function Module Value Manufacturing Engineering BoM E/E Software 23

24 Evaluation and Optimization Modelling and simulation is based on function and modules 2013 IAS, Universität Stuttgart 24

25 Contents Vision State-of-the-Art: Technologies in Automotive Research activities Example of Smart Factory and Agent-based control Identification of Mechatronic Objects Moving Design to Runtime Conclusion 2014 IAS, Stuttgart University 25

26 Moving Design to Runtime Smart engineering through learning and self-configuration Method: Configuration of automation systems through an agentbased Configuration of preconceived Components. => Flexible and Re-configurable Challenge of learning from the perspective of the engineer Keep system compliant with changing requirements Boundaries Auto-configuration, Learning 2014 IAS, Stuttgart University 26

27 Layer 1 Layer 2 Layer 3 Prof. Dr.-Ing. Michael Weyrich Learning Architecture (Example of industrial image processing) System target Optimization Simulation Optimization Simulation-based optimization of models (closed loop control) Observer Parameter adjustment Adaption layer Observation for parameter adjustment (open loop control) Image Processing Classifier Quality Execution layer Image processing with classifier Automation system Product recognition Products / Work pieces Sorted Products Camera-guided robot 2014 IAS, Stuttgart University 27

28 Quelle: Prof. Christian Müller-Schloer, Leibnitz Univ. Hannover, Vortrag Organic-Computing Quo vadis? ; Prof. Dr.-Ing. Michael Weyrich Citation of the DFG SPP: Organics Computing 2014 IAS, Stuttgart University 28

29 Contents Vision State-of-the-Art: Technologies in Automotive Research activities Example of Smart Factory and Agent-based control Identification of Mechatronic Objects Moving Design to Runtime Conclusion 2014 IAS, Stuttgart University 29

30 Seamless integration of Automation Technology Information technology has reached a stage from which disruptive changes of existing paradigms can be expected Coordination of the Internet of Things new concepts for architecture and middleware M2M machines can communicate with other devices, new standards for fieldbuses and wireless networks may come up Autonomous Decisions self-management and self-adjustments in the sense of independent action Human Machine Interface (HMI) seamless integration of SmartPhone and Apps Intelligent data processing sensors aggregate data and report the semantics of system conditions Virtual Engineering design and evaluation of systems in an augmented reality Knowledge Processing Computer based modelling of knowledge with deductive reasoning 2014 IAS, Stuttgart University 30

31 Research Revolving around the application domain Leading questions: How to compose automated systems effectively? Control of Decentralized Systems / Multi-agent systems as a control paradigm Identification methodologies for new Mechatronic Objects Adaptation and learning How to ensure dependability and safety of systems? Evaluation, Test of systems (level of maturity etc.) 2014 IAS, Stuttgart University 31

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